Browser automation with Playwright MCP for web navigation, form interaction, and data extraction.
Works with
Supports navigation, element interaction (click, type, select), screenshots, and accessibility snapshots that return element references for precise targeting
Includes JavaScript execution via browser_evaluate and multi-step atomic operations through browser_run_code for complex workflows
Requires --shared-browser-context flag to maintain browser state across sequential commands; server r
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbrowsing-with-playwrightExecute the skills CLI command in your project's root directory to begin installation:
Fetches browsing-with-playwright from bilalmk/todo_correct and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate browsing-with-playwright. Access via /browsing-with-playwright in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Automate browser interactions via Playwright MCP server.
# Using helper script (recommended)
bash scripts/start-server.sh
# Or manually
npx @playwright/mcp@latest --port 8808 --shared-browser-context &
# Using helper script (closes browser first)
bash scripts/stop-server.sh
# Or manually
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_close -p '{}'
pkill -f "@playwright/mcp"
Important: The --shared-browser-context flag is required to maintain browser state across multiple mcp-client.py calls. Without it, each call gets a fresh browser context.
# Go to URL
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_navigate \
-p '{"url": "https://example.com"}'
# Go back
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_navigate_back -p '{}'
# Accessibility snapshot (returns element refs for clicking/typing)
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_snapshot -p '{}'
# Screenshot
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_take_screenshot \
-p '{"type": "png", "fullPage": true}'
Use ref from snapshot output to target elements:
# Click element
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_click \
-p '{"element": "Submit button", "ref": "e42"}'
# Type text
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_type \
-p '{"element": "Search input", "ref": "e15", "text": "hello world", "submit": true}'
# Fill form (multiple fields)
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_fill_form \
-p '{"fields": [{"ref": "e10", "value": "[email protected]"}, {"ref": "e12", "value": "password123"}]}'
# Select dropdown
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_select_option \
-p '{"element": "Country dropdown", "ref": "e20", "values": ["US"]}'
# Wait for text to appear
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_wait_for \
-p '{"text": "Success"}'
# Wait for time (ms)
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_wait_for \
-p '{"time": 2000}'
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_evaluate \
-p '{"function": "return document.title"}'
For complex workflows, use browser_run_code to run multiple actions in one call:
python3 scripts/mcp-client.py call -u http://localhost:8808 -t browser_run_code \
-p '{"code": "async (page) => { await page.goto(\"https://example.com\"); await page.click(\"text=Learn more\"); return await page.title(); }"}'
Tip: Use browser_run_code for complex multi-step operations that should be atomic (all-or-nothing).
Run: python3 scripts/verify.py
Expected: ✓ Playwright MCP server running
pgrep -f "@playwright/mcp"bash scripts/start-server.shSee references/playwright-tools.md for complete tool documentation.
| Issue | Solution |
|---|---|
| Element not found | Run browser_snapshot first to get current refs |
| Click fails | Try browser_hover first, then click |
| Form not submitting | Use "submit": true with browser_type |
| Page not loading | Increase wait time or use browser_wait_for |
| Server not responding | Stop and restart: bash scripts/stop-server.sh && bash scripts/start-server.sh |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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I recommend browsing-with-playwright for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for browsing-with-playwright matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: browsing-with-playwright is focused, and the summary matches what you get after install.
Useful defaults in browsing-with-playwright — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
browsing-with-playwright has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added browsing-with-playwright from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
browsing-with-playwright fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
browsing-with-playwright reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: browsing-with-playwright is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: browsing-with-playwright is focused, and the summary matches what you get after install.
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